Bibliographic record
Abstract
Parts of a U.S. Route 44 relocation project span across cranberry bog areas with deep peat deposits. The peat in the proposed roadway side was completely excavated and backfilled with granular soils, and using sheet pile walls as retaining structures. As peat exhibits low strength, high compressibility, and significant creep behavior, the long-term performance of the sheet pile walls was a great concern. To monitor the development of sheet pile deflections and total lateral earth pressures in peat, selected sheet piles located in peat deposits were instrumented with pressure cells and inclinometer casings. Furthermore, to understand the soil–structure interaction mechanism during roadway construction, the finite element (FE) code PLAXIS was employed to continuously model roadway construction in peat deposits. Peat was simulated by a soft soil creep (SSC) model, which can account for creep effects. One of the challenges in this simulation was how to model deep dynamic compaction (DDC), since the enormous momentum induced by DDC would cause local failure of the soil body and consequently result in termination of the program. This problem was satisfactorily solved by using a dynamic approach presented in this paper, and the FE-calculated results were compared with the field measurements. The comparison indicated that FE modeling yields predictions in a good agreement with field measurements and also could provide some reasonable explanations for the field observations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".